神经网络的综合基础（第2版）英文原版

    本书详细分析了最知名的人工神经网络(ANN)模型，对它们进行了富有成果的比较，尤其注意从系统论和统计学的角度分析问题。

1,Introduction 2,Learning processes 3,single layer perceptrons 4,Multiayer perceptrons 5,Redial-Basis function networks 6,support vector machines 7,committee machines 8,principal components Analysis 9,self-organizing maps 10,information-theoretic models 11,stochastic machines and their approximates rooted in statistical mechanics 12,Neurodynamic programming 13,Temporal processing using feedforward networks 14,neurodynamics 15,Dynamically driven recurrent networks